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Enabling better global research outcomes in soil, plant & environmental monitoring.

Cropscan MSRSYS 16 Wavebands

It has been found that remote sensing using the MSRSYS16R multispectral radiometer is much more efficient and accurate for estimating severity of disease than the conventional visual rating methods. The MSRSYS16R multispectral radiometer is effective for estimating the loss in yield due to different levels of disease than is the plot combine. The radiometer is also useful for estimating the efficacy of different rates and timing of fungicide application and for screening of experimental fungicides in field trials.

FEATURES
• Upward and downward facing sensors (no need to carry white panel reference in field)
• Can be used in lightly cloudy conditions
1-16 bands (choose from a list of 116 bands in 460-1700 nm)
• Interfaces with the CROPSCAN Data Logger Controller
• Light weight and completely portable
• Can be used in stand-alone unattended operation

APPLICATIONS
• Describe:  normal plant growth and plant canopy colour
• Estimate crop biomass, biochemical content, crop yield components, crop quality factors, leaf area index and crop yield and quality.
Also estimate loss due to disease, insect infestation, air pollution, nutrient deficiencies, chemical phytotoxicity, etc.
• Evaluation of plant growth modifiers
• Objective and efficient rating of foliar disease
• Monitoring effects of herbicide activity
• Soil amendment and fertility studies
• Leaf feeding studies
• Irrigation scheduling studies
• Effects of drought on plant growth and yield
• Characterisation of different genotypes
• Evaluation of experimental area variability
• Ground truth for Remote Sensing

Radiometer

Wavebands: 1-16
Centre Wavelengths: Chose from list of 116 bands in 460-1700 nm range
Bandwidths: Narrowbands (~10 nm) to widebands (~300 nm)
Operating Range: 0 to +50°C, 0 to 100% RH non-condensing, <20% RH storage
Reflectance Range: 0 to 100%
Resolution: 0.06%
Accuracy: ±4%
Detectors: Photodiodes
Size: 80 x 80 x 100 mm
Weight: 0.68 kg

Data Logger Controller (DLC)

Operating Range: -40 to +70°C, 0 to 100% RH non-condensing
Resolution: 12 bits
Accuracy: ±0.4%
Number of Channels: 16 RS232 Serial Cables to PC or CT100 Hand Terminal
Size: 248 x 178 x 28 mm
Weight: 1.4 kg

Power

Battery Type: NiMH, 10V, 1.6 Ah battery pack, located in DLC, powers complete system
Operational Capacity: 9 hours on full charge
AC Adapter: Use overnight to recharge batteries

THEORY OF OPERATION

Every substance emits, absorbs, transmits or reflects electromagnetic radiation in a manner characteristic of the substance. This is the underlying principle involved in all remote sensing. By measuring the quantity of radiation absorbed, transmitted or reflected in each of the wavelengths, the characteristics of the substances can be defined. In practice, only certain selected wavelength bands need to be chosen to discriminate between selected characteristics of substances. For the CROPSCAN Multispectral Radiometer (MSR) System, narrow band interference filters are used to select certain bands in the visible and near infrared (NIR) regions of the electromagnetic spectrum. This region is useful for quantifying the reflectivity of plant canopies as affected by stresses of various kinds. The NIR bands of 750-900 nm are particularly useful for detecting and estimating the severity of foliar disease of plants. Longer wavelengths in the NIR may be useful for estimating biochemical content of plants.

SYSTEM OPERATION

In the field the radiometer is held level by the support pole above the crop canopy. The diameter of the field of view is one half of the height of the radiometer above the canopy. The data acquisition program included with the system facilitates digitising the voltages and recording percent reflectance for each of the selected wavelengths. The program also allows for averaging multiple samples. Ancillary data such as plot number, time, level of incident radiation and temperature within the radiometer may be recorded with each scan. Each scan, triggered by a manual switch or by pressing the space key on a terminal or PC, takes about 2 seconds. An audible beep indicates the beginning of a scan, two beeps indicate the end of scan and 3 beeps indicate the data is recorded in RAM. Data recorded in the RAM file are identified by location, experiment number and date. The design of the radiometer allows for near simultaneous inputs of voltages representing incident as well as reflected irradiation. This feature permits accurate measurement of reflectance from crop canopies when sun angles or light conditions are less than ideal. Useful measurements of percent reflectance may even be obtained during cloudy conditions. This is a very useful feature, especially when travelling to a remote research site only to find the sun obscured by clouds.

Cropscan Multispectral Radiometer References
Csillag, F., Kertész, M., Davidson, A. and Mitchell, S. 2001, ‘On the Measurement of Diversity-productivity Relationships in a Northern Mixed Grass Prairie (Grasslands National Park, Saskatchewan, Canada)’, Community Ecology, vol. 2, no. 2, pp. 145-159.

Dudka, M., Langton, S., Shuler, R., Kurle, J. and Grau, C.R. 1998, Use of Digital Imagery to Evaluate Disease Incidence and Yield Loss Caused by Sclerotinia Stem Rot of Soybeans, Proc. of the 1998 International Precision Agriculture Conference, St. Paul, MN. pp. 9 pp.

Elwadie, M.E., Pierce, F.J. and Qi, J. 2005, ‘Remote Sensing of Canopy Dynamics and Biophysical Variables Estimation of Corn in Michigan’, Agronomy Journal, vol. 97, pp. 99-105.

Green, D.E., Burpee, L.L. and Stevenson, K.L. 1998, ‘Canopy Reflectance as a Measure of Disease in Tall Fescue’, Crop Science, vol. 28, pp. 1603-1613.

Heidmann, T., Thomsen, A. and Schelde, K. 2000, ‘Modelling Soil Water Dynamics in Winter Wheat using Different Estimates of Canopy Development’, Ecological Modelling, vol. 129, pp. 229-243.

Li, H., Lascano, R.J., Barnes, E.M., Booker, J., Wilson, L.T., Bronson, K.F. and Segarra, E. 2001, ‘Multispectral Reflectance of Cotton Related to Plant Growth, Soil Water and Texture, and Site Elevation’, Agronomy Journal, vol. 93, pp. 1327-1337.

Ma, B.L., Dwyer, L.M., Costa, C., Cober, E.R. and Morrison, M.J. 2001, ‘Early Prediction of Soybean Yield from Canopy Reflectance Measurements’, Agronomy Journal, vol. 93, no. 6, pp. 1227-1234.

Ma, B.L., Subedi, K.D. and Costa, C. 2005, ‘Comparison of Crop-Based Indicators with Soil Nitrate Test for Corn Nitrogen Requirement’, Agronomy Journal, vol. 97, pp. 462-471.

Nebeker, T.E. and Evans, D.L. 2000, Determination and Demonstration of Remote Sensing Capabilities in Detecting and Monitoring Defoliation, Mortality and Disturbances Over Forested Landscapes, RSTC Mississippi State University: 10 pp.

Olson, K.C., Cochran, R.C. and Towne, G. 1995, Estimation of Forage Production Using Multispectral Radiometry. Proceedings from KSU Range Field Day, October 27, 1995. Manhattan, Kansas, Cooperative Extension Service, Kansas State University: 115-118.

Tarr, A.B., Moore, K.J. and Dixon, P.M. 2005, ‘Spectral Reflectance as a Covariate for Estimating Pasture Productivity and Composition’, Crop Science, vol. 45, pp. 996-1003.

Vigier, B. 2001, ‘Spatial Analysis of White Mold Infection in Soybean using Canopy Reflectance. Abstracts, The Canadian Phytopathological Society Annual Meeting, London, Ontario’, Canadian Journal of Plant Pathology, vol. 23, pp. 194-210.

Vrindts, E., Reyniers, M., Darius, P., De Baerdemaeker, J., Gilot, M., Sadaoui, Y., Frankinet, M., Hanquet, B. and Destain, M.-F. 2003, ‘Analysis of Soil and Crop Properties for Precision Agriculture for Winter Wheat’, Biosystems Engineering, vol. 85, no. 2, pp. 141-152.

Xue, L., Cao, W., Luo, W., Dai, T. and Zhu, Y. 2004, ‘Monitoring Leaf Nitrogen Status in Rice with Canopy Spectral Reflectance’, Agronomy Journal, vol. 96, no. 1, pp. 135-142.